Acta Geographica Sinica ›› 2021, Vol. 76 ›› Issue (4): 870-887.doi: 10.11821/dlxb202104007

• Urban Studies • Previous Articles     Next Articles

An analysis of the multidimensional globalizing city networks based on global value chain: A case study of iPhone suppliers

LIU Qing1(), YANG Yongchun1,2(), JIANG Xiaorong3, CAO Wanpeng1, LIU Xiaojie1   

  1. 1. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
    2. Key Laboratory of Western China's Environmental Systems, Ministry of Education of the People's Republic of China, Lanzhou University, Lanzhou 730000, China
    3. College of Resource Environmental and Tourism, Hubei University of Art and Science, Xiangyang 441053, Hubei, China
  • Received:2020-03-10 Revised:2020-07-22 Online:2021-04-25 Published:2021-06-25
  • Contact: YANG Yongchun;
  • Supported by:
    National Natural Science Foundation of China(41971198);National Natural Science Foundation of China(41571155)


Based on the data of 197 suppliers of iPhone components and parts in 2019, this paper builds multidimensional world city networks from the perspective of global value chains, integrating specialized cities with global functions and the high-class world cities into the same analytical framework, which enriches the research perspective of world city networks in the era of globalization to a certain extent. The purpose of this paper is to expand the research and investigation scope of the existing field of world city networks. By means of social network analysis (i.e. the analysis of centrality, connectedness and network cohesion), rank-size rule and community detection, we study the power and prestige, the overall topological structure, the community structure and influence mechanism of the city networks of R&D-oriented, production-oriented and OEM service-oriented types. The results show that: (1) All the world city networks are characterized by polycentricity and diversification, differentiation of nodes' status and dependence on external connections. The "star" nodes in the network coexist with high power and high prestige, and the power is generally higher than the prestige. (2) The network cohesion and rank of R&D-oriented cities are the highest, and the network tends to show a primate city distribution, and the growth of small group structure and the phenomenon of R&D clusters are obvious. The production-oriented network has the highest connectedness, and it tends to present a rank-size distribution and an equilibrium structure. Its network scale is large, but the ties of many nodes are sparse and decentralized; OEM service-oriented network has the highest relative centrality, and power and information are concentrated in a few city nodes. (3) The cluster characteristics of R&D-oriented city communities are most noticeable. Moreover, the network has significant long-distance knowledge spillover and cooperation behavior. Enterprises form specialized clusters in R&D-type cities through non-tradable interdependence, and obtain the benefits of localization economies and spatial integrated effects. The cluster tendency of production-oriented city communities are relatively obvious. Geographical proximity and spatial dependence are the main factors incubating community structure. Enterprises form generalized clusters through tradable interdependence to obtain the benefits of urbanization economies and distance attenuation effect. No obvious cluster network has been incubated in OEM serviced-oriented city communities. Polarization phenomenon of the inter-community is extremely significant, that is to say, the core city community in Taiwan, China, radiates to other low-level equilibrium communities, forming a radial community structure. Contract manufacturers seek the cities with low labor costs around the world to carry out standardized production, and realize full competition through scale economies, therefore, a scatter-type city network layout structure is formed.

Key words: globalizing city networks, global value chain, iPhone suppliers, social network analysis, community detection